File size: 3,526 Bytes
a703588 7f07db8 a703588 46cde66 778d09e ceb0714 46cde66 f9f8d44 dcfa366 3866637 dcfa366 a703588 ceb0714 778d09e ceb0714 778d09e 281b6e6 46cde66 a703588 dcfa366 a703588 dcfa366 f9f8d44 dcfa366 5f32ca7 dcfa366 5f32ca7 5ba3309 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 |
from flask import Flask,request,render_template,send_file,jsonify
import os
from transformers import AutoTokenizer, AutoModel
import anvil.server
import pathlib
import textwrap
import google.generativeai as genai
import import_ipynb
from library import call_gpt, call_gemini
from background_service import BackgroundTaskService
anvil.server.connect('PLMOIU5VCGGUOJH2XORIBWV3-ZXZVFLWX7QFIIAF4')
app=Flask(__name__)
MESSAGED={'title':'API Server',
'messageL':['published server functions:','encode(text)', 'call_gemini(text)']}
tokenizer = AutoTokenizer.from_pretrained('allenai/specter')
encoder = AutoModel.from_pretrained('allenai/specter')
# GOOGLE_API_KEY=os.getenv('GOOGLE_API_KEY')
# genai.configure(api_key=GOOGLE_API_KEY)
service=BackgroundTaskService(max_tasks=10)
service.register(call_gpt)
service.register(call_gemini)
@anvil.server.callable
def launch(func_name,*args):
global service
# Launch task
task_id = service.launch_task(func_name, *args)
print(f"Task launched with ID: {task_id}")
return task_id
@anvil.server.callable
def poll(task_id):
global service
# Poll for completion; if not complete return "In Progress" else return result
result = service.get_result(task_id)
if result=='No such task': return str(result)
elif result!='In Progress':
del service.results[task_id]
if isinstance(result, (int, float, str, list, dict, tuple)):
return result
else:
print(str(result))
return str(result)
else: return str(result)
# @anvil.server.callable
# def call_gemini(text):
# model = genai.GenerativeModel('gemini-pro')
# response = model.generate_content(text)
# return response.text
@anvil.server.callable
def encode_anvil(text):
inputs = tokenizer(text, padding=True, truncation=True,
return_tensors="pt", max_length=512)
result = encoder(**inputs)
embeddings = result.last_hidden_state[:, 0, :]
emb_array = embeddings.detach().numpy()
embedding=emb_array.tolist()
return embedding
@app.route('/encode',methods=['GET','POST'])
def encode():
print(request)
if request.method=='GET':
text=request.args.get('text')
elif request.method=='POST':
data=request.get_json()
if 'text' in data: text=data["text"]
if text=='' or text is None: return -1
inputs = tokenizer(text, padding=True, truncation=True,
return_tensors="pt", max_length=512)
result = encoder(**inputs)
embeddings = result.last_hidden_state[:, 0, :]
emb_array = embeddings.detach().numpy()
embedding=emb_array.tolist()
return jsonify({'embedding': embedding})
@app.route("/file/<string:filename>")
def return_file(filename):
return send_file('./data/'+filename)
@app.route('/run',methods=['GET','POST'])
def run_script():
script=''
# print(request.method)
print(request)
if request.method=='GET':
script=request.args.get('script')
print('I am in get')
elif request.method=='POST':
print('I am in post')
data=request.get_json()
if 'script' in data: script=data['script']
if script=='' or script is None: return 'INVALID'
os.system(script+' > ./out.txt')
with open('./out.txt','r') as f: output=f.read()
return output
@app.route('/',methods=['GET', 'POST'])
def home():
return render_template('home.html',messageD=MESSAGED)
if __name__=='__main__':
app.run(host="0.0.0.0", port=7860)
|